r - 根据R中的查找表填充列

Question

假设我有以下“关键”数据集:

key = read.table(text = "question r_answer d_answer
                  20 A B
                  21 B A 
                  22 A B
                  23 B A
                  24 A B
                  25 B A", header = T)

> key
  question r_answer d_answer
1       20        A        B
2       21        B        A
3       22        A        B
4       23        B        A
5       24        A        B
6       25        B        A

这告诉我，对于给定的问题，“R”会给出什么答案，“D”会给出什么答案。

现在让我们说这是数据集:

data =  read.table(text = "person_id question answer
1 20 A
1 21 B
1 22 A
1 23 B
1 24 A
1 25 B
2 20 A
2 21 A
2 23 A
2 24 B
2 25 B", header = T)

>data
   person_id question answer
1          1       20      A
2          1       21      B
3          1       22      A
4          1       23      B
5          1       24      A
6          1       25      B
7          2       20      A
8          2       21      A
9          2       23      A
10         2       24      B
11         2       25      B

这告诉我，对于给定的人，他们的实际答案是什么。我想创建一个 answer_type数据中的列等于 r_answer或 d_answer取决于键中列出的值。结果输出将是:

   person_id question answer answer_type
1          1       20      A    r_answer
2          1       21      B    r_answer
3          1       22      A    r_answer
4          1       23      B    r_answer
5          1       24      A    r_answer
6          1       25      B    r_answer
7          2       20      A    r_answer
8          2       21      A    d_answer
9          2       23      A    d_answer
10         2       24      B    d_answer
11         2       25      B    r_answer

我有一种感觉，答案将涉及从 dplyr 合并，但我不太清楚。

Answer 1

一 dplyr和 tidyr选项可以是:

data %>%
 left_join(key %>%
            pivot_longer(-question, names_to = "answer_type"), by = c("question" = "question",
                                                                      "answer" = "value"))

   person_id question answer answer_type
1          1       20      A    r_answer
2          1       21      B    r_answer
3          1       22      A    r_answer
4          1       23      B    r_answer
5          1       24      A    r_answer
6          1       25      B    r_answer
7          2       20      A    r_answer
8          2       21      A    d_answer
9          2       23      A    d_answer
10         2       24      B    d_answer
11         2       25      B    r_answer